distilbert_lda_100_v1_qqp

This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_100_v1 on the GLUE QQP dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3133
  • Accuracy: 0.8600
  • F1: 0.8240
  • Combined Score: 0.8420

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 256
  • eval_batch_size: 256
  • seed: 10
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Combined Score
0.4043 1.0 1422 0.3275 0.8511 0.7992 0.8252
0.2918 2.0 2844 0.3133 0.8600 0.8240 0.8420
0.2305 3.0 4266 0.3147 0.8715 0.8340 0.8527
0.179 4.0 5688 0.3178 0.8760 0.8279 0.8520
0.1389 5.0 7110 0.3525 0.8805 0.8365 0.8585
0.1067 6.0 8532 0.3905 0.8783 0.8409 0.8596
0.086 7.0 9954 0.4037 0.8788 0.8427 0.8608

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.2.1+cu118
  • Datasets 2.17.0
  • Tokenizers 0.20.3
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Dataset used to train gokulsrinivasagan/distilbert_lda_100_v1_qqp

Evaluation results